Return pre and post counts in all the ROIs given bodyids innervate.
neuprint_get_roiInfo(
bodyids,
dataset = NULL,
all_segments = FALSE,
chunk = TRUE,
progress = FALSE,
conn = NULL,
...
)
the body IDs for neurons/segments (bodies) you wish to query.
This can be in any form understood by neuprint_ids
.
optional, a dataset you want to query. If NULL
, the
default specified by your R environ file is used or, failing that the
current connection, is used. See neuprint_login
for details.
if TRUE, all bodies are considered, if FALSE, only 'Neurons', i.e. bodies with a status roughly traced status.
A logical specifying whether to split the query into multiple
chunks or an integer specifying the size of those chunks (which defaults
to 2000 when chunk=TRUE
).
default FALSE. If TRUE, the API is called separately for
each neuron and you can assess its progress, if an error is thrown by any
one bodyid
, that bodyid
is ignored
optional, a neuprintr connection object, which also specifies the
neuPrint server. If NULL, the defaults set in your
.Rprofile
or .Renviron
are
used. See neuprint_login
for details.
methods passed to neuprint_login
a dataframe, one row for each given body id, columns ROI_pre and ROI_post for every ROI. If data is missing, NA is returned.
# \donttest{
neuprint_get_roiInfo(c(818983130, 1796818119))
#> # A tibble: 2 × 17
#> bodyid LH(R)…¹ LH(R)…² MB(R)…³ MB(R)…⁴ CA(R)…⁵ CA(R)…⁶ MB(+A…⁷ MB(+A…⁸ SNP(R…⁹
#> <int> <int> <int> <int> <int> <int> <int> <int> <int> <int>
#> 1 8.19e8 210 97 75 14 75 14 75 14 5
#> 2 1.80e9 283 117 77 16 77 16 77 16 NA
#> # … with 7 more variables: `SNP(R).post` <int>, `SLP(R).pre` <int>,
#> # `SLP(R).post` <int>, `mALT(R).pre` <int>, `mALT(R).post` <int>,
#> # `AL(R).pre` <int>, `AL(R).post` <int>, and abbreviated variable names
#> # ¹`LH(R).pre`, ²`LH(R).post`, ³`MB(R).pre`, ⁴`MB(R).post`, ⁵`CA(R).pre`,
#> # ⁶`CA(R).post`, ⁷`MB(+ACA)(R).pre`, ⁸`MB(+ACA)(R).post`, ⁹`SNP(R).pre`
# }